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The Agile Brand with Greg Kihlström®: Expert Mode Marketing Technology, AI, & CX
#698: Staying customer-centric in the race to adopt agentic AI with Stephanie Liu, Forrester
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- [00:00]
Greg Kilstrom
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Unknown Host
The Agile Brand.
- [01:15]
Greg Kilstrom
Welcome to Season seven of the Agile Brand where we discuss the trends and topics marketing leaders need to know. Stay curious, stay agile and join the top enterprise brands and Martech platforms as we explore marketing technology, AI, e commerce and whatever's next for the Omnichannel customer experience. Together we'll discover what it takes to create an agile brand built for today and tomorrow and built for customers, employees and continued business growth. I'm your host Greg Kilstrom, advising Fortune 1000 brands on martech, AI and marketing operations. To to make sure you always get the latest episodes, please hit subscribe on the app you listen to podcasts on and leave us a rating so others can find us as well. Now onto the show.
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Unknown Host
If your roadmap doesn't include your customer, is it really a roadmap or just.
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Greg Kilstrom
A bridge to nowhere?
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Unknown Host
We're here at Forester CX in Nashville, Tennessee and hearing all about the latest insights and ideas for brands to create better experiences for their customers. Agility requires remembering who pays the bills the customer. When shiny new tech shows up, it's tempting to sprint after it, often leaving the actual human in our dust. Today we're talking about staying customer first in the race to adopt agentic AI. To help me dig in, please welcome Stephanie Liu, Senior Analyst at Forrester. Stephanie, welcome to the show.
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Stephanie Liu
Thanks for having me.
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Unknown Host
Yeah, looking forward to talking about this with you. Before we dive in though, why don't we start with you giving a little background on yourself and the researcher Leading at Forrester.
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Stephanie Liu
Sure. So I'm a senior analyst. I'm actually on Forrester's B2C marketing team and I cover the intersection of privacy and marketing. And that has expanded over the years to include the customer data ecosystem, customer data strategy, and now AI agents in terms of the data pieces and the privacy pieces.
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Unknown Host
Got it, got it. Okay. Well, yeah, you're the right person to be talking about this topic with here and definitely I can see why it might have expanded over the years as well. But yeah, let's, let's get started with talking about agentic AI. Certainly. I mean, first it was AI had to be. There was an unwritten rule that had to be mentioned in every single episode of my show. Now agentic is certainly coming along and it certainly seems to be everywhere already, but a lot of consumers have never heard of the term. What's the very first thing that brands need to make sure that they get right to stay genuinely customer first while they experiment with something like agentic AI?
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Stephanie Liu
The annoying answer is it's two things. One is to really define what you're trying to do with AI. Peel back the hype, what is the use case, what are your outcomes you're working towards? And the second is to, as you said in the upfront, don't leave your customer behind. I think there's a lot of emphasis right now on how AI can benefit the business. There's a lot of noise around productivity and efficiency. Don't leave your customers in those conversations. Think about the value exchange for them. How will AI benefit the customer in terms of the experience or, you know, the interaction, the personalization, whatever it is, there needs to be an upside for the customer as well.
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Unknown Host
Yeah, yeah. A lot of times though, the upside for customers, you know, getting more personalized experiences and everything involves having more data around from that customer. And so, you know, there is this. The value exchange, you know, has got to be balanced with, you know, with some of the privacy issues and things that you work on as well. Only 23% of us online adults are comfortable sharing personal data with gen AI tools. How can marketers narrow that trust gap without, you know, without stalling their innovation?
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Stephanie Liu
Yeah, I think the most important thing to remember is that most people don't understand AI. I have to remind clients of this a lot because it's a bit of like a self selection issue. You're at Forrester CX conference. You are coming to my track sessions on AI. You're clearly more invested in this just by being here than by a lot of Consumers themselves. And so it's, if you are going to introduce an AI driven experience to a customer, you have to explain what, what it is, why they should use it and what's in it for them. Right. So that's the value exchange piece. But then the second piece of that is to really emphasize the data piece, only collecting what you need to deliver that value. Once we get into the we want to know everything about you for some vague promise of personalization. Right. That's really recreating the mistakes we made of 10 years ago when we were just collecting everything and seeing what stuck. And, and that's why data deprecation and privacy regulations rolled in. So it's really a matter of again, emphasizing that use case and mapping out what data you need to ask from the customer to deliver on that use case.
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Unknown Host
Yeah, yeah. And so Forrester has something called privacy Personas. I want to get a definition on that from you as well. But these can help brands tailor their AI rollouts. Can you talk a little bit? You know, what do we mean by privacy Persona? And how can brands work with this so that they can tailor their AI rollouts and really help streamline things?
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Stephanie Liu
Sure. So I'll give you the backstory on why we built these Personas in the first place. We used Forrester's proprietary data on consumers and what we were trying to do was bust the myth that people either care about privacy or they. The reality is it's a lot more nuanced. There are folks who share data freely, but there are also folks, we call them conditional consumerists. They will share data if you incentivize them. So for example, they love loyalty programs because there is a clear sign up for the program, share some information, get points. Right. And then at the far end of the spectrum, we call them skeptical protectionists. They're the we do not want to share our data. We are very tech savvy and very, very protective. And so when it comes to designing for these Personas, you have to remember that all of them are represented in your customer base. That group that shares data freely, they're reckless rebels. They're only about 1/3 of us online adults. For the other 2/3, you have to think about the value proposition to pull in those conditional consumerists and how to treat the folks who are very averse to AI and don't want to use it. And so one of the challenges there's is you can't make AI mandatory because you will end up pulling some customers away from you. Right. And it may actually end up in, you know, they're trying to escalate through human channels and they're getting more aggressive about it because there's more AI in their way. So I do think it's important to understand the balance there of AI can help you. But if you want the human touch, if you really don't like AI or you don't understand it, or you're just not tech savvy, that there's still a way for you to get what you need, whether that's information or customer support.
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Unknown Host
Yeah, yeah. I mean it sounds like making AI mandatory, you're potentially alienating a third of your audience.
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Greg Kilstrom
Right?
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Unknown Host
Yeah, yeah. So then even to take things further, you know, there's been a few announcements recently about things like online shopping agents and things like that that are acting on consumers behalf or will soon enough. Most of us are not quite there yet, sending the AIs out to do our shopping for us. And that level of trust a little bit to your last point. So before AI is going to be fully acting on a customer's behalf, we're kind of in this intermediary phase. So context aware. We've been talking about personalization and things like that for years. But now with AI potentially taking things further, yet still not fully autonomous, what does a human centric experience look like in this kind of middle ground that we're in?
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Stephanie Liu
Yeah, so this middle ground is actually really interesting because I think this is our chance to build trust without going full agentic, full autonomy, because the risks of full autonomy are much greater. Right. So thinking about this pretty relatively confined use case and capability where what can we do with it today to improve the experience. And again, thinking about this from the customer's perspective, not the brand's, to get them to grow a little bit more comfortable with AI so that when it does become more autonomous, when there is more capability behind it, the consumer is brought along on that journey. Realistically, this isn't going to be one day there's a flip of a switch and ta da, agentic is here. It's going to creep up on us through these incremental improvements in the underlying agentic AI capabilities. And again, consumers are not tracking these developments as closely as tech vendors and as agencies and brands. So it's really about bringing them along the journey, getting them comfortable with where we are today so that they're not shocked by what's coming tomorrow.
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Unknown Host
Yeah. Is transparency about when AI is being used? I mean, is that part of this as well?
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Stephanie Liu
Definitely, yes. People don't like to be deceived which is we actually did a market research online community panel about this and you know, how would you feel if a brand was using, using AI and didn't disclose it? And the number one response was deceived or angry or upset. And then there were a couple that were very confident of that would never happen. I always know when it's AI and I think they're in for a rude awakening.
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Greg Kilstrom
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Unknown Host
So as from the, from the brand perspective then you know, when rolling these things out, I mean there's, there's good ways to do this, there's bad ways to do this, but you know, regardless of the method, what KPIs or maybe leading signals even should leaders and others watch to know when something that might be an experiment or a pilot project is really ready to roll out to a larger audience?
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Stephanie Liu
Yeah, so this is where defining your use case very narrowly is really, really important. And when I say narrowly, I mean right now, sometimes it is as specific as one step in a broader workflow. If we think about the way Genai rolled out, it initially was just producing content, right? Given these Instructions, go produce 800 variants of whatever. As we've grown more comfortable with Genai as it's gotten better, it's not creating people with seven fingered hands anymore. It's moving upstream. And now it's part of the creative brief process, right? Like do some research on the opportunity, the audience, et cetera, et cetera. It's going to be something like that with these AI agent pilots. Can you do this one step in the workflow and can you do it well? And by that I mean is it behaving as expected? Is it producing accurate outputs? Is it pulling from up to date data or is it pulling from stale, outdated data? If it can prove that, then it's not like, all right, we're going to launch this to the broader world. I think it's more, can we move it upstream in the process. And I do think we'll start with internal use cases because the risk is a lot lower. And once we master those, then I think brands will start to experiment with the customer facing ones. If you look at customer service, which is where a lot of AI hype is happening right now, it's very similar. The early use cases are about automating the customer agent work, not necessarily interfacing with the customer to resolve their conflict because there's just too many unknowns, too many variables there.
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Unknown Host
Yeah, I mean to me it reminds me of early days of ChatGPT and Genai. It's like if you asked a very, very broad question or gave it a very, very broad prompt, you kind of get what now we all expect is you get something that's not very good and it could go in many different directions. Right. So I mean, Agentix seems a similar approach of you need to be very specific. In my experience, it's actually helped me think through processes in different and more thorough ways than I thought I did before. So it's actually, there's actually been some personal growth there, but that's probably a topic for a different show. But I mean is, is. It sounds like you're saying something similar in that it's, you know, take it one case at a time kind of build. It's almost like the Lego blocks or whatever, like build it one piece at a time and you're building not only trust, but you're building those, you know, you're, you're building according to the KPIs kind of one step at a time. Is that, does that sound right?
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Stephanie Liu
That's exactly right. And when I talk to clients, I mean this was the whole theme of my track session on AI agents. They are not real today, they are not autonomous, they're not wonderfully doing all these decisioning and actions, but they're coming. And so what we can do today is peel back the hype on all the wonderful things we'll do and just think about how do we get ready for that future. And that readiness stage is really, it's going through the nuts and bolts of what data we need, what tools it needs access to and what teams we need to work with. Because realistically there is not going to be a single department that can run the whole thing and build the whole thing. There won't be one data set. That is all the AI agent needs. And I think identifying those pieces, it's again, it's not fun work, it's not glamorous. But it will put you in a much stronger position to be ready when you know, agentic AI is fully agentic.
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Unknown Host
Yeah. And to talk about the team and the team structures and things like that, what do you recommend there? You know, what have you seen that's worked even in early tests or something when we're talking about these broad reaching things?
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Greg Kilstrom
Silos don't work.
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Unknown Host
We know that already from, from other, you know, from Journey orchestration or other things like that even. But you know, what does work and what should leaders be thinking about?
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Stephanie Liu
The frustrating thing is there's no single answer. A lot of it depends on the organization, their risk tolerance and so on. But one approach I've seen that I really do like, it comes from a highly regulated industry. They have a centralized. It's like an AI governance council. And if you want to build an AI agent, however you're defining that fully agentic or not, you have to pitch your idea to this council. And what I really like about it is it forces you to go through that critical thinking of how are we going to explain the use case and the KPIs and what we're trying to do here? Right. It peels back again, appeals back the hype of like efficiency and is getting into the nuts and bolts. And what's also nice about this council is they can flag, hey, that sounds a lot like this AI agent that, you know, that Greg built. You should go talk to him and see if you can copy what he's done or if your use case is actually so unique that you need your own. And what I think is nice about that is there are companies, some really big tech companies right now that are hyping up how easy it is to build an AI agent and it unlocks a lot of opportunity. But I also think there's some risk there of waste and of duplication. Right. If you have folks who are building AI agents for the same workflow, for example, or the same process, if they are doing that independently, then you're wasting a lot of resources, both financially and computationally on running AI agents in parallel. So that centralized governance structure is nice, but ultimately it's still on the team pitching the AI agent to deploy it. And so they still have control over the spec and what it's trying to do. But that governance council adds that layer of accountability and of cross functional collaboration to try and combat some of those duplication issues, as well as security and privacy issues, of course.
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Unknown Host
Yeah, yeah, I love that. Yeah. And it also kind of eliminates some of the hype of like we just because we can doesn't. I mean we should. But also I love the idea of just being able to share because I've worked in those large organizations where there are two people working on almost exactly the same thing that I've never met before. And yeah, it's at best it's a waste and at worst it's just a real missed opportunity to learn and grow and innovate. So yeah, I love that. Well, a couple of last things here. You know, we're here on the ground at Forester CX in Nashville so far. I know we're only in day two here, but what's the single most insightful thing that you've heard or seen at the conference so far and why did it stick with you?
- [19:05]
Stephanie Liu
I'd have to say it was Kelsey Chickering's keynote where she compared consumers to toddlers. And I have a toddler is very accurate. But it was like consumers are impulsive. We want instant gratification. And there were a couple others in there. But the whole point was that when you're deliver, it's not just the customer experience, it's also the brand experience and really what the brand perception is and how all both sides of that equation will impact the customer and how they perceive your brand and how they experience the brand. And so I thought it was a really well done analogy and it's one that gave me a good chuckle.
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Unknown Host
Yeah, yeah, yeah, that was great. Yeah. I actually interviewed her this morning so she's going to be on the show as well. Stephanie, thanks so much for sharing your ideas and insights. One last question for you before we wrap up. What do you do to stay agile in your role and how do you find a way to do it consistently?
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Stephanie Liu
Ah, I don't know if this is a good lead to follow, but I try to say yes to as many things as I can. And I find that being outside of my comfort zone is actually where agility is the most important. And so I try to push what I'm comfortable doing like a podcast interview at the Forrester conference.
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Greg Kilstrom
You're doing great by the way, but.
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Stephanie Liu
I think it's good to challenge yourself and really make sure you're not getting too comfortable because I do think that's where innovation and agility, where they happen organically.
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Unknown Host
Yeah, I love that. Well, Stephanie, thanks so much for sharing everything today. Again, I'd like to thank Stephanie Liu, senior analyst at Forrester, for joining the show here at Forrester CX in Nashville, Tennessee. You can learn more about Stephanie and Forrester by following the links in the show. Notes.
- [20:56]
Greg Kilstrom
Thanks again for listening to the Agile Brand. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show as well. You can access more episodes of the show@theagilebrand.com that's theagile brand.com and contact me. If you're interested in consulting or advisory services or are looking for a speaker for your next event, go to www.gregkilstrom.com. that's G R E G K I H L S t r o m.com the Agile brand is produced by Missing Link, a Latina owned, strategy driven, creatively fueled production co op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. Until next time, stay curious and stay agile.
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Unknown Host
The Agile Brand.
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Greg Kilstrom
Before we continue, I wanted to share a key strategic resource that a majority of the Fortune 500 are already aware of. Finding the best technology, business and talent solutions is not easy. With business demands and competitive pressures mounting, you need to be able to design, deploy and optimize your technology to provide leading customer experiences while driving business growth. Those of you that have been listening to this show for a while know that this podcast is brought to you by Tech Systems, a global provider of technology, business and talent solutions for more than 80% of the Fortune 500. Tech Systems accelerates business transformation for their customers. Whether you're looking to maximize your technology roi, drive business growth, or elevate customer experiences, Tech Systems enables enterprises to capitalize on change. Learn more@techsystems.com that's teksystems.com now let's get back to the show.